Abstract
This paper proposes an adaptive optimal policy for hourly operation of an energy storage system (ESS) in a grid-connected wind power company. The purpose is to time shift wind energy to maximize the expected daily profit following uncertainties in wind generation and electricity price. A stochastic dynamic programming (SDP) framework is adopted to formulate this problem, and an objective function approximation method is applied to improve the SDP computational efficiency. Case studies on the Electric Reliability Council of Texas demonstrate that the resultant profits from SDP-based operation policy are considerably higher than those from deterministic policy, and comparable to those from the perfect information model. It is concluded that the presented SDP approach can provide operation policy highly adaptive to uncertainties arising from wind and price. The proposed framework can help the wind company optimally manage its generation with ESS.
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